style: apply black formatting

Author: web-flow

packages/parser-core/src/bankstatements_core/extraction/boundary_detector.py

@@ -9,7 +9,10 @@
 import logging
 from dataclasses import dataclass
 
-from bankstatements_core.extraction.row_classifiers import RowClassifier, create_row_classifier_chain
+from bankstatements_core.extraction.row_classifiers import (
+    RowClassifier,
+    create_row_classifier_chain,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -66,7 +69,11 @@ def __init__(
         self.columns = columns
         self.fallback_bottom_y = fallback_bottom_y
         self.table_top_y = table_top_y
-        self._row_classifier = row_classifier if row_classifier is not None else create_row_classifier_chain()
+        self._row_classifier = (
+            row_classifier
+            if row_classifier is not None
+            else create_row_classifier_chain()
+        )
 
         # Configuration parameters
         self.min_gap_threshold = min_section_gap

packages/parser-core/src/bankstatements_core/extraction/pdf_extractor.py

@@ -248,7 +248,11 @@ def _determine_boundaries_and_extract(
             )
 
             dynamic_bottom_y = detect_table_end_boundary_smart(
-                all_words, table_top_y, self.columns, table_bottom_y, row_classifier=self._row_classifier
+                all_words,
+                table_top_y,
+                self.columns,
+                table_bottom_y,
+                row_classifier=self._row_classifier,
             )
 
             # Safety check: Cap dynamic boundary at static boundary to prevent over-extraction

packages/parser-core/tests/extraction/test_boundary_detector.py

@@ -387,7 +387,9 @@ def test_injected_classifier_is_used(self):
 
         mock_chain = Mock(spec=RowClassifier)
         mock_chain.classify.return_value = "metadata"
-        detector = TableBoundaryDetector(columns=TEST_COLUMNS, row_classifier=mock_chain)
+        detector = TableBoundaryDetector(
+            columns=TEST_COLUMNS, row_classifier=mock_chain
+        )
         words = [{"text": "Footer", "x0": 60, "top": 350}]
         detector.detect_boundary(words)
         mock_chain.classify.assert_called()